The SNePS Research Group SNeRG Prof. Stuart C.

The SNePS Research Group SNeRG Prof. Stuart C.

The SNePS Research Group

SNeRG

Prof. Stuart C. Shapiro, Prof. William J. Rapaport
Prof. Carl Alphonce, Prof. Josephine Anstey, Prof. Debra T. Burhans, Prof. Michelle L. Gregory, Prof. Jean-Pierre A. Koenig, Prof. David R. Pierce
Graduate Students: Jonathan Bona, Trupti Devdas Nayak, Albert Goldfain, Frances L. Johnson, Michael Kandefer, John F. Santore, Lunarso Sutanto
Undergraduate Students: Vikranth B. Rao, Isidore DingaMadou

Semantic Network Processing System
The long-term goal of The SNePS Research Group is the design and construction of a natural-language-using computerized cognitive agent, and carrying out the research in artificial intelligence,
computational linguistics, and cognitive science necessary for that endeavor. The three-part focus of the group is on knowledge representation, reasoning, and natural-language understanding
and generation. The group is widely known for its development of the SNePS knowledge representation/reasoning system, and Cassie, its computerized cognitive agent.

Cassie the FEVAHR Agent

GLAIR Architecture

A Plan for Detonating Unexploded
Landmines (UXOs)

Grounded Layered Architecture with Integrated Reasoning
Knowledge Level

NL

SNePS
Perceptuo-Motor Level

Sensory-Actuator Level

Natural Language Interaction with
FEVAHR (Foveal Extra-Vehicular
Activity Helper-Retriever) Cassie

Vision
Sonar
Motion

: Who are you?

all(a)(Agent(a) =>
ActPlan(Blowup(a, UXOs),
Act(a,
Cascade(SearchforUxo(a),
WithSome+(obj,
Near(a, obj),
WithNew({ch ex},
{Charge(ch), Explosion(ex)},
Possess(a, ch),
Cascade(Place(a, ch, obj),
Hide(a),
Waitfor(a, ex),
SearchforUxo(a))),
goto(a, SafeZone))))))

My name is `Cassie'

Proprioception

and I am the SNePS cognitive agent.

Example SNePS Ontology

: Who did you talk to?
I talked to Stu
and I talked to Bill
and I talked to Carl
and I talked to David
and I talked to Debbie
and I talked to J.P.
and I talked to Josephine
and I talked to Michelle
and I am talking to you.
: Who did you see?

The Trial The Trail is an

I saw Stu

interactive drama for an immersive
VR environment. Its intelligent agents
are SNePS-driven.

and I saw Albert
and I saw Fran
and I saw John
and I saw Jon
and I saw Lunarso
and I saw Michael
and I saw Trupti

Contextual Vocabulary Acquisition:From Algorithm to Curriculum

and I see you.

Belief Base Revision with Reconsideration

UAV

PIs: William J. Rapaport (CSE & SNeRG) & Michael W. Kibby (Learning & Instruction Dept.)
CVA = computing a meaning for unknown word from contextual clues & prior knowledge

Current Belief Base
Time

UAV

INTEL

TROOPS

T1

Red in D1,D2

Red in D1,D3

T2

Red in D1,D2

Red in D1,D3,C3,Bridge-D

T3

Red in D1,D2

Red in D1,D3,C3,D4

Always

TROOPS > UAV > INTEL

Always

TROOPS > INTEL > UAV

INTEL
Red in C3

Asserting beliefs into the belief base (or KB) = Adding them to the KB = Stating them to
be true.
T1: UAV & INTEL disagree on Red troop location => contradiction.
Consolidation makes a belief base consistent -- in this case by removing (or retracting)
INTELs statement. = Contracting the KB by INTELs statement. (UAV > INTEL)
T2: UAV & INTEL again disagree.
At T3, BLUE TROOPS confirm an INTEL belief over that of UAV
So, we reverse the INTEL/UAV credibility order. Thus, UAV is disbelieved.
Reconsideration of the KB is defined as consolidation of all base beliefs (current, or not).
INTELs earlier beliefs are recaptured (= returned to the KB), and UAVs are retracted.

Identifying Perceptually Indistinguishable Objects:
Is that the same one you saw before?

Crystal Cassies view of the world showing two perceptually indistinguishable robots,
one of whom she is following.

BLUE
TROOPS

There came a white hart running into the hall with a white brachet next to him, and thirty couples of black hounds came running
after them. As the hart went by the sideboard, the white brachet bit him. The knight arose, took up the brachet and rode away
with the brachet. A lady came in and cried aloud to King Arthur, Sire, the brachet is mine. There was the white brachet which
bayed at him fast. The hart lay dead; a brachet was biting on his throat, and other hounds came behind. [Morte DArthur]
Cassie learns what brachet means: From above text + prior knowledge about harts, animals, King Arthur, etc.; no info
about brachetsInput: SNePS version of simplified English narrative. Output: Definition frame (varies with context and prior
knowledge):
1.First Sentence:
A hart runs into King Arthurs hall.
3. Full Story:
In the story, B12 is a hart.
A hart runs into King Arthurs hall.
In the story, B13 is a hall.
A white brachet is next to the hart.
In the story, B13 is King Arthurs.
The brachet bites the harts buttock.
In the story, B12 runs into B13
The knight picks up the brachet.
A white brachet is next to the hart.
The knight carries the brachet.
In the story, B14 is a brachet.
The lady says that she wants the brachet.
In the story, B14 has the property white.
The brachet bays at Sir Tor.
Therefore, brachets are physical objects.
+ prior knowledge: only hunting dogs bay
deduced while reading, using
4.--> (defineNoun brachet)
prior knowledge: only physical objects have color Definition of brachet:
2.--> (defineNoun brachet)
Class Inclusions: hound, dog,
Definition of brachet:
Possible Actions: bite buttock, bay, hunt,
Class Inclusions: phys obj,
Possible Properties: valuable, small, white,
Possible Properties: white,
5. OED: brachet: a kind of hound which hunts by scent
Application: Development of classroom curriculum to teach CVA, based on our CVA algorithms

Robots used in human subjects and Crystal Cassies
tasks

What Crystal Cassie can see: a table with glasses and a computer lab with two people

SNeRG website: www.cse.buffalo.edu/sneps

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